Biomedical Engineering and Bioengineering Commons^™

The Subject Librarian Newsletter, Engineering And Computer Science, Fall 2017, Buenaventura "Ven" Basco

Buenaventura "Ven" Basco

No abstract provided.

Person Identification From Streaming Surveillance Video Using Mid-Level Features From Joint Action-Pose Distribution, Binu M. Nair, Vijayan K. Asari

Vijayan K. Asari

We propose a real time person identification algorithm for surveillance based scenarios from low-resolution streaming video, based on mid-level features extracted from the joint distribution of various types of human actions and human poses. The proposed algorithm uses the combination of an auto-encoder based action association framework which produces per-frame probability estimates of the action being performed, and a pose recognition framework which gives per-frame body part locations. The main focus in this manuscript is to effectively combine these per-frame action probability estimates and pose trajectories from a short temporal window to obtain mid-level features. We demonstrate that these mid-level …

Video-To-Video Pose And Expression Invariant Face Recognition Using Volumetric Directional Pattern, Vijayan K. Asari, Almabrok Essa

Vijayan K. Asari

Face recognition in video has attracted attention as a cryptic method of human identification in surveillance systems. In this paper, we propose an end-to-end video face recognition system, addressing a difficult problem of identifying human faces in video due to the presence of large variations in facial pose and expression, and poor video resolution. The proposed descriptor, named Volumetric Directional Pattern (VDP), is an oriented and multi-scale volumetric descriptor that is able to extract and fuse the information of multi frames, temporal (dynamic) information, and multiple poses and expressions of faces in input video to produce feature vectors, which are …

Gaussian Nonlinear Line Attractor For Learning Multidimensional Data, Theus H. Aspiras, Vijayan K. Asari, Wesam Sakla

Vijayan K. Asari

The human brain’s ability to extract information from multidimensional data modeled by the Nonlinear Line Attractor (NLA), where nodes are connected by polynomial weight sets. Neuron connections in this architecture assumes complete connectivity with all other neurons, thus creating a huge web of connections. We envision that each neuron should be connected to a group of surrounding neurons with weighted connection strengths that reduces with proximity to the neuron. To develop the weighted NLA architecture, we use a Gaussian weighting strategy to model the proximity, which will also reduce the computation times significantly. Once all data has been trained in …

Review Of Emg-Based Speech Recognition, Amean Al_Safi, Liqaa Alhafadhi

Amean S Al_Safi

This study represents a review of the main studies in EMG-based speech recognition. Its main goal is to support the researchers in the biomedical field with a survey of the solved and unsolved problem in the direction since it has received a great attention during last decade due to its promise applications such as underwater communication and silent speech recognition. Hence this study is a very good starting point for the researchers interested in this area of research

Using Finite State Machine And A Hybrid Of Eeg Signal And Eog Artifacts For An Asynchronous Wheelchair Navigation

Faculty of Engineering University of Malaya

In this study, an asynchronous wheelchair navigation system using a hybrid of EEG signal and EOG artifacts embedded in EEG signals is demonstrated. The EEG signals are recorded at three different locations on the scalp in the occipital and motor cortex regions. First, an EEG signal related to eyelid position is analyzed and used to determine whether the eyes are closed or open. If the eyes are closed, no wheelchair movement is allowed. If the eyes are open, EOG traces (artifacts) from two other EEG signals are examined to infer the gaze direction of the eyes. A sliding window is …

Estimating Effective Connectivity From Fmri Data Using Factor-Based Subspace Autoregressive Models, Chee-Ming Ting Phd, Abd-Krim Seghouane Phd, Sh-Hussain Salleh Phd, Alias M. Noor Phd

Chee-Ming Ting

Estimation Of High-Dimensional Brain Connectivity From Fmri Data Using Factor Modeling, Chee-Ming Ting Phd, Abd-Krim Seghouane, Sh-Hussain Salleh, Alias M. Noor

Chee-Ming Ting

We consider identifying effective connectivity of brain networks from fMRI time series. The standard vector autoregressive (VAR) models fail to give reliable network estimates, typically involving very large number of nodes. This paper adopts a dimensionality reduction approach based on factor modeling, to enable effective and efficient high-dimensional VAR analysis of large network connectivity. We derive a subspace VAR (SVAR) model from the factor model (FM) in which the observations are driven by a lower dimensional subspace of common latent factors, following an autoregressive dynamics. We consider the principal components (PC) method which can produce consistent estimators for the FM, …

Estimating Dynamic Cortical Connectivity From Motor Imagery Eeg Using Kalman Smoother & Em Algorithm, S. Balqis Samdin, Chee-Ming Ting Phd, Sh-Hussain Salleh, Mahyar Hamedi, Alias Mohd Noor

Chee-Ming Ting

This paper considers identifying effective cortical connectivity from scalp EEG. Recent studies use time-varying multivariate autoregressive (TV-MAR) models to better describe the changing connectivity between cortical regions where the TV coefficients are estimated by Kalman filter (KF) within a state-space framework. We extend this approach by incorporating Kalman smoothing (KS) to improve the KF estimates, and the expectation-maximization (EM) algorithm to infer the unknown model parameters from EEG. We also consider solving the volume conduction problem by modeling the induced instantaneous correlations using a full noise covariate. Simulation results show the superiority of KS in tracking the coefficient changes. We …

Pre-Amplifiers For A 15-Tesla Magnetic Resonance Imager, Chin-Leong Lim, Peter Serano, Jerome L. Ackerman

Chin-Leong Lim

High-field magnetic resonance imagers (MRI) give better signal-to-noise ratio (SNR) and image contrast. However clinical MRIs are currently limited to 3 Tesla (T) magnetic field strength. To create an uncommon 15 T scanner for research use, we evaluated several low-cost, intended for wireless communication, GaAs enhancement-mode pseudomorphic high electron mobility transistors (ePHEMT) in the critical preamplifier slot. This paper reports the experimental results that were obtained at both module and system levels. When evaluated in our prototype 15 T scanner front-end’s preamplifier slot, the candidate devices’ sub 1dB noise figures enabled image SNR ~ 110 in a water phantom (test …

Development Of A Novel Handheld Device For Active Compensation Of Physiological Tremor, Abhijit Saxena

Abhijit Saxena

In microsurgery, the human hand imposes certain limitations in accurately positioning the tip of a device such as scalpel. Any errors in the motion of the hand make microsurgical procedures difficult and involuntary motions such as hand tremors can make some procedures significantly difficult to perform. This is particularly true in the case of vitreoretinal microsurgery. The most familiar source of involuntary motion is physiological tremor. Real-time compensation of tremor is, therefore, necessary to assist surgeons to precisely position and manipulate the tool-tip to accurately perform a microsurgery. In this thesis, a novel handheld device (AID) is described for compensation …

Parallel Recording Of Neurotransmitters Release From Chromaffin Cells Using A 10 X 10 Cmos Ic Potentiostat Array With On-Chip Working Electrodes, Brian Kim, Adam Herbst, Sung Kim, Bradley Minch, Manfred Lindau

Bradley Minch

Neurotransmitter release is modulated by many drugs and molecular manipulations. We present an active CMOS-based electrochemical biosensor array with high throughput capability (100 electrodes) for on-chip amperometric measurement of neurotransmitter release. The high-throughput of the biosensor array will accelerate the data collection needed to determine statistical significance of changes produced under varying conditions, from several weeks to a few hours. The biosensor is designed and fabricated using a combination of CMOS integrated circuit (IC) technology and a photolithography process to incorporate platinum working electrodes on-chip. We demonstrate the operation of an electrode array with integrated high-gain potentiostats and output time-division …

Nanoenabled Microelectromechanical Sensor For Volatile Organic Chemical Detection, Chiara Zuniga, Matteo Rinaldi, Samuel M. Khamis, A. T. Johnson, Gianluca Piazza

Matteo Rinaldi

A nanoenabled gravimetric chemical sensor prototype based on the large scale integration of single-stranded DNA (ss-DNA) decorated single-walled carbon nanotubes (SWNTs) as nanofunctionalization layer for aluminum nitride contour-mode resonant microelectromechanical (MEM) gravimetric sensors has been demonstrated. The capability of two distinct single strands of DNA bound to SWNTs to enhance differently the adsorption of volatile organic compounds such as dinitroluene (simulant for explosive vapor) and dymethyl-methylphosphonate (simulant for nerve agent sarin) has been verified experimentally. Different levels of sensitivity (17.3 and 28 KHz µm^2/fg) due to separate frequencies of operation (287 and 450 MHz) on the same die have also …

Field Programmable Gate Arrays To Accelerate Sub-Surface Imaging Problems, Miriam Leeser

Miriam Leeser

No abstract provided.

Patient Safety: What Can Be Done About It?, Steven Dain

Steven L Dain

Much is said and written about patient safety. In Canada, a small group of dedicated physicians, nurses and engineers participates in the Canadian Standards Association and Standards Council of Canada Advisory Committees writing basic safety and essential performance requirements for a large range of anesthesia, respiratory care and critical care equipment. Over the past several years, in recognition of the globalization of trade and the international nature of medical device design and manufacturing, Canadian Anesthesiologists’ Society members Dr Steven Dain, Dr Karen Brown, Dr Matt Kurrek, Dr Ken LeDez, and Dr Jeremy Sloan have primarily participated in Organization for International …

Nanoenabled Microelectromechanical Sensor For Volatile Organic Chemical Detection, Chiara Zuniga, Matteo Rinaldi, Samuel M. Khamis, A. T. Johnson, Gianluca Piazza

Matteo Rinaldi

A nanoenabled gravimetric chemical sensor prototype based on the large scale integration of single-stranded DNA (ss-DNA) decorated single-walled carbon nanotubes (SWNTs) as nanofunctionalization layer for aluminum nitride contour-mode resonant microelectromechanical (MEM) gravimetric sensors has been demonstrated. The capability of two distinct single strands of DNA bound to SWNTs to enhance differently the adsorption of volatile organic compounds such as dinitroluene (simulant for explosive vapor) and dymethyl-methylphosphonate (simulant for nerve agent sarin) has been verified experimentally. Different levels of sensitivity (17.3 and 28 KHz µm^2/fg) due to separate frequencies of operation (287 and 450 MHz) on the same die have also …

Deconvolution Of Compartmental Water Diffusion Coefficients In Yeast-Cell Suspensions Using Combined T1 And Diffusion Measurements, Matthew D. Silva, Karl G. Helmer, Jing-Huei Lee, Sam S. Han, Charles S. Springer, Christopher H. Sotak

Sam Han

Deconvolution of Compartmental Water Diffusion Coefficients in Yeast-Cell Suspensions Using Combined T1 and Diffusion Measurements